PROJECT SUMMARY/ABSTRACT Identifying potential targets for interventions to reduce age-related cognitive morbidity in diverse elders is of critical importance to the rapidly expanding aging population in the U.S. Substantial evidence from observational studies suggest that modifiable positive psychosocial factors (i.e., well-being, self-efficacy, social support) are associated with better cognitive functioning among older adults. These effects are independent of negative affect (e.g., depression). However, little attention has been given to subgroups of older adults who are particularly vulnerable to age-related cognitive morbidity: African Americans, Hispanics, and individuals with mild cognitive impairment (MCI). In addition, it is unclear whether these positive psychosocial factors buffer against the negative cognitive effects of brain pathology, as measured with structural magnetic resonance imaging. This K99/R00 proposal lays the foundation for an independent research career focused on characterizing the mechanisms underlying psychosocial factors that protect against age-related cognitive morbidity among a diverse population. Together, the research and training plans will provide the applicant (1) supplementary training in modeling neuroimaging biomarker data in an aged population, (2) broader experience with psychosocial variables in aging, and (3) a strong foundation in cross-cultural neuropsychology. These experiences will supplement the applicant's strong existing background in geriatric neuropsychology and quantitative methods. The research plan expands an existing community-based longitudinal study of multi-ethnic older adults at Columbia University. This diverse population is followed every 18-24 months with cognitive testing, medical evaluation, health measures, and consensus diagnoses of MCI/dementia. A subset receive structural neuroimaging. This proposal adds well-validated, computer-based measures of psychosocial functioning and cognition from the NIH Toolbox. Cross-sectional and longitudinal structural equation models (SEM) will test relationships between positive psychosocial factors, cognition, and quantitated measures of hippocampal volume, regional cortical thickness, white matter hyperintensity volume, and infarcts. The primary goal is to characterize the role of positive psychosocial factors in late-life cognitive decline and to determine whether they reduce the impact of structural MRI markers of brain pathology on cognitive functioning.